Search Results (2,663)

Green fintech operates at the intersection of sustainable finance, digital innovation, and financial-sector risk governance. It promises to improve the allocation of capital toward environmentally sustainable activities by lowering information costs, scaling disclosure tools, automating environmental verification, and widening access to green investment products. Yet the same digital features that make green fintech attractive—speed, scalability, data intensity, platform intermediation, cross-border distribution, and algorithmic decision-making—can also transform apparently local regulatory weaknesses into broader financial-stability concerns. This article examines how regulatory risk associated with green fintech may evolve into systemic risk under conditions of market concentration, weak data governance, regulatory fragmentation, greenwashing amplification, and financial interconnectedness. It develops a mechanism-based conceptual framework rather than an econometric test. The framework connects three regulatory dimensions—regulatory clarity and scope, supervisory consistency, and innovation facilitation—with five systemic-risk transmission channels: market concentration, data and model risk, regulatory arbitrage, greenwashing amplification, and financial interconnectedness. The article draws on sustainable-finance regulation, the financial-stability literature, fintech scholarship, and official supervisory documents, including the EU Sustainable Finance Disclosure Regulation, the EU Taxonomy Regulation, the Digital Operational Resilience Act, and the ESG Ratings Regulation. The central argument is cautious but policy-relevant: green fintech does not automatically create systemic risk, but regulatory uncertainty and supervisory gaps may become systemic when they are embedded in digital infrastructures that scale quickly and are relied upon by multiple financial institutions. The article contributes to risk scholarship by shifting the analysis from compliance-level regulatory risk to transmission mechanisms through which green-finance innovation may affect market integrity and financial stability. Full article

Sustainable finance has evolved rapidly in tandem with digital transformation and the circular economy; however, the simultaneous integration of these three domains remains fragmented. This study analyzes the intellectual structure of the field through a bibliometric analysis of a curated corpus of 2537 articles indexed in Scopus between 2015 and 2025, of which 2471 were classified into three thematic trajectories: sustainable finance combined with digital transformation (D1), sustainable finance combined with the circular economy (D2), and triadic convergence (D3). The classification followed a deductive, rule-based procedure, with documents independently coded by the two authors and discrepancies resolved by consensus. VOSviewer was used to construct networks of keyword co-occurrence, co-citation, and bibliographic coupling, identifying four thematic clusters. A complementary keyword-overlap projection was then used to articulate the deductive classification with the inductive clusters. The results reveal a rapidly expanding field, geographically concentrated in China, in which the dyadic trajectories anchor predominantly in a single conceptual cluster, while triadic convergence (D3), which appears only in 2021 and accounts for 2.7% of the classified corpus, is the only trajectory whose documents distribute across three clusters simultaneously. This pattern provides empirical support for interpreting triadic convergence as an emerging frontier rather than a consolidated stream. The findings are interpreted under the lens of economicità, an Italian accounting concept that frames sustainability as a condition for the firm’s long-term economic equilibrium. Full article

This study investigates the relationship between climate change and financial risk by examining how temperature variations affect banking sector credit quality across European Union countries. Using quarterly panel data and sector-level non-performing loan (NPL) ratios from the EBA Risk Dashboard, the paper applies fixed-effects and dynamic panel models to estimate climate–credit sensitivities. Specifically, we investigate whether observed temperature changes affect sectoral NPLs in Europe and whether these effects differ across sectors. The results indicate a statistically significant and positive relationship between temperature changes and NPL levels, with notable heterogeneity across sectors. Evidence further suggests that climate shocks exhibit delayed effects on credit risk, as models incorporating lag structures yield stronger and more robust results. These findings provide empirical support for integrating climate variables into credit risk assessment and contribute to the literature by offering a sector-resolved, data-driven foundation for climate risk stress-testing frameworks. Full article

Morocco has developed one of the most comprehensive sustainability governance architectures among middle-income emerging economies, yet the relationship between its formal regulatory ambition and on-the-ground implementation effectiveness remains poorly understood. This narrative literature review provides an integrated, critically analytical account of Morocco’s sustainability governance system, organised around three interlocking dimensions: (i) a progressively strengthened legislative corpus anchored by the 2011 Constitution and Framework Law 99-12; (ii) a portfolio of national sustainability strategies aligning domestic policy with Paris Agreement commitments, Nationally Determined Contributions (NDCs), and the United Nations Sustainable Development Goals (SDGs); and (iii) corporate sustainability practices driven by regulatory obligations, international supply chain pressures, and ESG disclosure norms. Drawing on 124 sources, comprising 62 peer-reviewed articles, 38 legislative texts, and 24 institutional reports, and applying institutional isomorphism theory as an integrating analytical lens, the review advances three theoretical propositions concerning the conditions under which formal governance architectures translate into effective sustainability outcomes. It further proposes a validated conceptual framework and develops a comparative positioning of Morocco against peer economies (Tunisia, Egypt, South Africa, and Turkey). Critical implementation gaps are identified in enforcement capacity, SME integration, sustainability data infrastructure, and green finance, contributing a balanced and evidence-grounded assessment of Morocco’s sustainability transition. These findings offer actionable insights for policymakers, regulators, and business leaders operating in the Moroccan and broader African context. Full article

Rural electrification in Sub-Saharan Africa faces a trilemma: cutting carbon emissions, making it economically viable, and achieving fair access to energy for all. This paper develops a multi-objective framework that optimises carbon revenue, net present value (NPV), total energy supply, cooking fuel (firewood and LPG), health costs, and benefit to society. The model uses continuous decision variables: daily energy allocation among four sources (solar, generator, firewood, LPG) to three population groups (men, women, children). The case study is a rural community of 7000 people in Nigeria (Tier 1 energy consumers). Six policy scenarios are considered: baseline, high carbon price, low carbon price, microfinance, government subsidy and community cooperative. This study compared algorithms and identified a hybrid Non-dominated Sorting Genetic Algorithm and Particle Swarm Optimisation II as the most suitable algorithm for solving the formulated optimisation problem. It was found that NPV and unit cost of energy would increase to $175,500 and 26.4 ¢/kWh, respectively, by increasing the price of carbon from $8/ton to $12/ton. Firewood generates health savings and carbon revenue in the range of $4100–$12,270/year. Prices below $8/ton do not induce optimal reconfigurations in the system. The best energy supply (2825 kWh/day) and the lowest unsatisfied demand occur in the government subsidy scenario with the greatest disparity index, displaying an equity-efficiency trade-off. The framework shows that sustainable access to energy can be unlocked using strategic integration of carbon finance, valuation of health benefits and equity constraints. Full article

Proper handling during harvesting and subsequent postharvest management is essential to reduce losses in fruits and vegetables, particularly because these products remain metabolically active after harvest. Physiological processes such as respiration, transpiration, ethylene production, softening, physiological disorders, and postharvest diseases determine quality deterioration, shelf life, and marketability. However, these processes do not affect all commodities in the same way; for example, climacteric fruits are strongly influenced by ethylene during ripening, whereas non-climacteric fruits generally show lower ethylene production and different postharvest behavior. In Mexico, postharvest management is especially relevant because fruit and vegetable producers differ widely in terms of production scale, infrastructure, access to technology, financing capacity, and market destination. Producers with limited access to technology require practical and low-cost alternatives, while more technologically advanced producers may use specialized systems but still experience postharvest losses due to physiological deterioration, handling conditions, logistics, and market constraints. Therefore, this review summarizes the main postharvest physiological processes affecting fruits and vegetables and discusses their implications for knowledge transfer, technology adoption, and sustainability among local producers in Mexico. The review highlights that reducing postharvest losses requires commodity-specific management, continuous technical support, low-cost and locally adaptable technologies, and coordinated participation among researchers, extension personnel, producers, government institutions, industry, and market actors. Strengthening postharvest knowledge transfer to small and local producers is essential to reduce losses, improve marketability, and promote more sustainable fruit and vegetable systems in Mexico. Full article

The transition toward sustainable manufacturing requires an understanding of how industrial policies shape firms’ long-term green innovation capabilities. This study investigates the impact of China’s intelligent manufacturing pilot policy on enterprises’ sustainable green innovation, conceptualizing the policy as an exogenous driver of systemic transformation at the firm level. Using multi-period difference-in-differences (DID) regression on an unbalanced panel dataset of Chinese listed companies from 2010 to 2023, we find that the intelligent manufacturing pilot policy exerts a significantly positive effect on enterprises’ sustainable green innovation. Mechanism analyses reveal that the policy promotes sustainable green innovation through three pathways: facilitating digital transformation, alleviating financing constraints, and enhancing ESG performance. Heterogeneity analysis further indicates that the policy effects are more pronounced in eastern regions, among non-state-owned enterprises, in non-heavily polluting industries, and in technology-intensive industries. These findings provide insights into how systemic policy interventions can drive sustainable innovation at the firm level, with implications for policymakers and enterprises seeking to align industrial upgrading with long-term green development. These findings are interpreted through a system transformation lens, where intelligent manufacturing policies trigger co-evolutionary changes across digital, financial, and governance subsystems. Full article

Climate change and low-carbon transition policies affect sustainable development by changing firms’ financing costs and investors’ capital allocation. This paper investigates whether and how climate-related information is priced in China’s equity market, focusing on firm-level carbon intensity and exposure to climate policy uncertainty (CPU). First, univariate-sorted portfolio tests confirm the existence of a carbon premium, as firms with high carbon intensity earn significantly higher average returns. However, the unconditional relation between CPU exposure and stock returns is insignificant. Bivariate-sorted portfolios reveal a strong interaction between the carbon premium and the CPU premium. The carbon premium is higher for firms with high exposure to CPU, whereas a significant and negative CPU premium appears among low-carbon firms and, in sector-level tests, is concentrated in non-energy firms. Further analysis demonstrates clear differences between energy and non-energy sectors, which may be attributable to cash flow risks and uncertainty in growth options. The findings contribute to climate-related asset pricing and sustainable finance research by showing that transition-risk pricing depends on the interaction between carbon exposure and policy uncertainty. Full article

This study examines the relationship between Environmental, Social, and Governance (ESG) performance and financing and pricing outcomes in green and conventional bond markets in China over the period of 2017–2024. Drawing on signaling theory, information asymmetry theory, and market segmentation theory, the study argues that the role of ESG performance differs across bond types because green and conventional bonds operate within different institutional and informational environments. Using a comparative analysis of green and conventional bonds, the findings show that ESG performance is more strongly and consistently associated with conventional bond characteristics, particularly in relation to issuance amount, yield to maturity, and credit spreads. In contrast, ESG effects in green bonds are weaker and less consistent, suggesting that investors place greater emphasis on certification mechanisms, environmental project objectives, and sustainability-related bond characteristics than on broader issuer-level ESG disclosures. The findings also suggest that ESG information does not affect all debt instruments in the same way or always functions as a purely risk-reducing signal. In the Chinese market, stronger ESG exposure may also be associated with transition risks, regulatory pressures, and sector-specific sustainability challenges, particularly in conventional bond markets. Overall, the results indicate that the financial relevance of ESG performance depends not only on firm characteristics but also on the institutional and informational environment of the financial instrument itself. The findings remain robust across alternative model specifications and sensitivity analyses, providing additional confidence in the reported differences between green and conventional bond markets. The study contributes to the sustainable finance literature by showing that the pricing relevance of ESG information is instrument-specific rather than uniform across debt markets. It also provides practical implications for regulators, investors, and issuers by highlighting the importance of disclosure quality, transparency standards, and external verification mechanisms in strengthening investor confidence and reducing potential greenwashing risks in sustainable finance markets. Full article

In the current context, where sustainability has become a global imperative, emerging markets have increasingly incorporated green finance as a strategic pillar to foster long-term growth and stability. This study examines the evolution, trends, and key challenges of sustainable investment in emerging economies, with a particular focus on the integration of environmental, social, and governance (ESG) criteria. A systematic literature review was conducted using Scopus and Web of Science, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, based on a sample of 399 articles published over the past decade. The findings reveal a significant expansion in academic output on ESG investments in emerging markets, with an average annual growth rate of 14.06% and an international co-authorship rate of 37.34%. China, the United Kingdom, South Africa, and the United States emerge as leading contributors, particularly since 2020. However, critical gaps persist, including inconsistencies in ESG ratings and the limited adaptation of ESG frameworks to local socioeconomic and institutional conditions. Future research should focus on strengthening public policy frameworks, designing effective fiscal incentives, assessing the distributive implications of green finance, and leveraging technologies such as fintech, blockchain, and artificial intelligence to enhance ESG rating consistency, transparency, risk measurement, and the overall efficiency of sustainable investments. Full article

To promote the sustainable development of agriculture and reduce resource waste, this paper investigates sustainable financing strategies for a green fresh agri-food supply chain. We employ a purely theoretical Stackelberg game model and numerical simulations based on hypothetical parameters to develop three financing models for a supply chain consisting of one capital-constrained farmer and one retailer, considering consumers’ dual sensitivity to product freshness and greenness. Analytical and numerical results reveal that: (1) with low financing rates, internal financing effectively alleviates under investment in preservation, leading to higher wholesale/retail prices. In a green-sensitive market, the resulting price premium compensates for cost increases, avoiding the “low quality–low price” trap under external financing. (2) The retailer’s total profit decreases as the internal financing rate rises; higher interest income cannot offset demand loss caused by reduced preservation effort. Thus, a low- or zero-interest strategy maximizes the retailer’s operational profit. (3) As consumer sensitivity to freshness and greenness increases, profit growth under internal financing displays convexity. However, under extremely high freshness sensitivity, external financing yields stronger marginal incentives, suggesting that retailers should adjust profit allocation in the high-end market. The findings provide theoretical guidance for financing mode selection and practical insights for promoting green agricultural sustainable development. Full article

Obtaining market approval and reimbursement are necessary but not sufficient conditions for the implementation of new vaccines in high-income countries to maximize their long-term preventative value. Comprehensive pre-launch and launch-phase economic evaluations of the disease and the vaccine are necessary to support long-term public health improvement by the vaccination program. This review highlights the construction of these evaluations conceived as a plan, methods, and a tool. They can be generated by different stakeholders (e.g., payers, producers, target groups) interested in the value success of vaccination. A Vaccine Launching Value Project (VLVP) has been developed based on the experience gained from helping to launch 10 new vaccines worldwide over 15 years (2005–2020). It comprises information on the following: (1) identification of new vaccines that should require a VLVP approach; (2) country-specific characteristics of healthcare; (3) methods to assess economic values for specific stakeholders; (4) identification of the money flow in managing the disease and infection spread; and (5) optimal implementation strategies at the initiation of new vaccination programs. The benefits of applying the VLVP are illustrated using rotavirus vaccination as an example. The VLVP program starts with the development of a Broad Country Linked Inventory (Brocoli) Plan that interconnects eight baskets of information specifying a framework of activities. This is followed by the Cauliflower and Artichoke Methods to assess the vaccine value for additional key stakeholders (e.g., employers, hospital managers, working mothers, the Ministry of Finance) and the money flow amongst the payers (who pays what to whom, when, for what, and how). The evaluation process finishes with the Total Management Tool (Tomato) to identify the optimal implementation conditions at the start of a new vaccination program necessary to obtain the best long-term value for the stakeholders selected. The critical interconnections between these information blocks are discussed. This improves the positioning of a new vaccine by articulating its total economic value within a societal and public health environment over time, outside the conventional Health Technology Assessment box. The Tomato Tool emerges as the most pivotal component of the VLVP. It provides the best assurance of long-term economic value with strong sustainability support. Full article

While rapid digital transformation has significantly optimized sectors such as finance and e-commerce, maintenance management in industrial environments has historically received lower levels of technological and capital investment. This lag creates critical gaps in operational efficiency and asset longevity, particularly within renewable energy infrastructures where sustainability and resilience are paramount. Addressing this technological disparity is essential for minimizing ecological footprints and maximizing the viability of net-zero systems. This paper introduces an advanced multi-platform digital solution designed to optimize the operation and maintenance of renewable energy systems and smart infrastructures. The platform addresses traditional management gaps by implementing standardized protocols that integrate real-time remote monitoring, sensor networks, and cloud-based data acquisition. By centralizing historical and real-time data from solar, wind, and hybrid grids, it facilitates advanced analytics, such as predictive modeling of component degradation. Real-world validation across photovoltaic plants and wind farms demonstrates significant impacts: a 30% reduction in unplanned outages and a 20% to 25% decrease in operational and maintenance costs. The results confirm that digitalizing maintenance processes is a strategic pillar for the energy transition, aligning industrial performance with global low-carbon pathways. Full article

The European Green Deal (EGD) is the European Union’s comprehensive growth strategy for achieving climate neutrality by 2050. It comprises 17 interrelated policy documents, spanning sectors from energy and transport to biodiversity and sustainable finance. Despite their collective importance, these documents are characterized by significant heterogeneity in structure, terminology, and scope, making it challenging for non-technical stakeholders to navigate, cross-reference, extract, and validate information across their corpus as a whole. Considering the limitations of Natural Language Processing (NLP) approaches targeting the accessibility of policy documents and the lack of prior work explicitly focusing on the EGD and sustainability, we introduce a graph retrieval-augmented generation (GraphRAG) pipeline for natural language question answering (QA) over the EGD corpus. Our contributions include the conceptualization of a generalizable entity type set for policy documents for the EGD and its representation in the form of a knowledge graph, the development of two novel graph-based retrieval strategies that exploit the pre-computed structural properties of the knowledge graph, and the release of a specialized evaluation dataset, built on persona profiles matching real-world user profiles. The implementation and evaluation of the proposed approach are detailed, highlighting its effectiveness for the analysis of policy documents for the EGD against other GraphRAG baselines. Full article

Artificial Intelligence (AI) is rapidly transitioning from a specialized technology to an everyday socio-technical infrastructure, yet public acceptance remains shaped by a trade-off between perceived benefits and risks. This study examines how individuals from varied demographic and professional backgrounds perceive, use, and evaluate AI-enabled systems using a mixed-method research design. A bilingual (English/Arabic) online survey ($N=115$) captured demographics, awareness, usage patterns, perceived impact, self-assessed understanding, domain-specific trust, concerns, and attitudes toward regulation, complemented by open-ended reflections. In parallel, semi-structured face-to-face interviews provided deeper insight into AI conceptualization, lived experiences, trust boundaries, and conditions for acceptable use. Quantitative results show frequent AI engagement embedded in daily life, with strong domain dependence in trust: education is the most trusted domain, whereas healthcare and finance attract substantially lower trust. Prominent concerns include overreliance (“brain rot”), privacy and data misuse, job displacement, and misinformation. Support for stronger AI regulation is high, indicating that governance is viewed as a prerequisite for sustainable adoption rather than a constraint on innovation. Qualitative findings triangulate these results, revealing a pattern of conditional acceptanceunderstood as the simultaneous valuation of AI’s practical utility alongside the imposition of explicit trust prerequisites whereby participants value AI for productivity and learning support while emphasizing confidentiality, transparency, human oversight in high-stakes contexts, and clear boundaries to mitigate misuse and erosion of human judgment. The study offers empirically grounded insights for policymakers, educators, and industry stakeholders into how AI acceptance is negotiated through utility, literacy, perceived risk, and expectations of accountability. Full article